Deregulation Of Electric Industry Research Articles

Power Transfer Capability Recognition in Deregulated System under Line Outage Condition Using Power World Simulator

The major challenges in deregulated system are determination of available transfer capability on the interconnected transmission lines. Electricity industry deregulation is the required for creating a competitive market throughout the world, which instigate new technical issues to market participants and Power System Operators (PSO). Power transfer capability is a crucial parameter to decide the power flow in the lines for further transactions and the estimation of Transfer Capability decides the power transactions based on the safety and ability of the system. This parameter will decide if an interconnected network could be reliable for the transfer of bulk power between two different areas of the network without causing risk to system consistency. The Power Transfer Distribution Factor (PTDF) is the sensitivity index, which decides the transfer capability in the interconnected network under deregulated power systems. This experiment is conducted on IEEE-6 bus system using Power World Simulator to determine the transfer capability in deregulated system under line outage condition.

Mathematical modelling of bio-inspired frog leap optimization algorithm for transmission expansion planning.

Bio-inspired computing has progressed so far to deal with real-time multi-objective optimization problems. The Transmission expansion planning of the modern electricity grid requires finding the best and optimal routes for electricity transmission from the generation point to the endpoint while satisfying all the power and load constraints. Further, the transmission expansion cost allocation becomes a critical and pragmatic issue in the deregulated electricity industry. The prime objective is to minimize the total investment and expansion costs while considering N-1 contingency. The most optimal transmission expansion planning problem's solution is calculated using the objective function and the constraints. This optimal solution provides the total number and best locations for the candidates. The presented paper details the mathematical modeling of the shuffled frog leap algorithm with various modifications applied to the method to refine the results and finally proposes an enhanced novel approach to solve the transmission expansion planning problem. The proposed algorithm produces the expansion plans based on target-based evolution. The presented algorithm is rigorously tested on the standard Garver dataset and IEEE 24 bus system. The empirical results of the proposed algorithm led to better expansion plans while effectively considering typical electrical constraints along with modern and realistic constraints.

Ambiguities and Nonmonotonicities under Prosumer Power: Optimal Distributed Energy Resource Investment in a Deregulated Electricity Industry

Ambiguities and Nonmonotonicities under Prosumer Power: Optimal Distributed Energy Resource Investment in a Deregulated Electricity Industry

De-Regulation of Electricity Industry: A Malaysian Perspective

The Malaysian electricity industry has gone through an evolution over the years from vertically integrated utility into a single buyer market model currently. Many countries have de-regulated their electricity industry to increase efficiency and to introduce electricity price competitiveness. It is a natural path for any developing country like Malaysia to evolve into a fully functional market with complementary commercial instruments, such as whole-sale, balance, and network access arrangements. However, Malaysia must take the right path in pursuing de-regulation through energy market, thus ensuring a smooth transition from regulated into de-regulated electricity industry. This paper analyzed the energy market operation of three different countries. The analysis was based on the drivers for regulation, how the de-regulation was introduced to the vertically integrated system, the market model and the structure. From the comparative analysis, the hybrid model which combines single buyer model and pool market seems to be the potential approach for Malaysia in its path to de-regulation.

Integrating Real Options Analysis with long-term electricity market models

In liberalized electricity markets, the investment postponement option is deemed decisive for understanding the addition of new generating capacity. Basically, it refers to the possibility for investors to postpone projects for a period while waiting for the arrival of new and better information about the market evolution. When such development involves major uncertainties, the generation business becomes riskier, and the investors' “wait-and-see” behavior might limit the timely addition of new power plants. In that sense, the literature provides solid empirical evidence about the occurrence of construction cycles in the deregulated electricity industry. However, the strategic flexibility inherent to the option to defer new power plants has not yet been rigorously incorporated to investment signals in existing market models. Therefore, this paper proposes a novel methodology to assess the long-term development of liberalized power markets based on a more realistic approach for valuing generation investments. The work is based on a stochastic dynamic market model, built upon System Dynamics simulation approach. The decision-making framework considers that the addition of new capacity is driven by the economic value of the strategic flexibility associated with deferring investments under uncertainties. Thus, the value of the postponement option is quantified in monetary terms through Real Options Analysis. Simulations confirm the cyclical behavior of the energy-only market in the long run, as suggested by the empirical evidence found in the literature. In addition, sensitivity analysis regarding some relevant exogenous variables depicts an even more fluctuating evolution of the capacity due to the combination of strong demand growth rates with large volatilities. Finally, the model validity is assessed through a formal procedure according to the scope of System Dynamics modeling approach.

Forecasting energy consumption in Tamil Nadu using hybrid heuristic based regression model

Energy consumption forecasting is vitally important for the deregulated electricity industry in the world. A large variety of mathematical models have been developed in the literature for energy forecasting. However, researchers are involved in developing novel methods to estimate closer values. In this paper, authors attempted to develop new models in minimizing the forecasting errors. In the present study, the economic indicators of the state including population, gross state domestic product, yearly peak demand, and per capita income were considered for forecasting the electricity consumption of a state in a developing country. Initially, a multiple linear regression model has been developed. Then, the coefficients of the regression model were optimized using two heuristic approaches namely genetic algorithm and simulated annealing. The mean absolute percentage error obtained for the three models were 2.00 for multiple linear regression model, 1.94 for genetic algorithm based linear regression and 1.86 for simulated annealing based linear regression.

Sustainable transmission planning in imperfectly competitive electricity industries: Balancing economic and environmental outcomes

We explore the role of a transmission system operator (TSO) that builds a transmission line to accommodate renewable energy in order to lower emissions as required by government policy. In contrast to central planning, a TSO in a deregulated electricity industry can only indirectly influence outcomes through its choice of the transmission line capacity. Via a bi-level model, we show that this results in less transmission capacity and with limited emissions control in a perfectly competitive industry vis-à-vis a benchmark centrally planned system. A carbon charge on industry that fully accounts for the cost of pollution damage leads to a perfect alignment of incentives and maximised social welfare only under perfect competition. By contrast, a carbon charge may actually lower social welfare under a Cournot oligopoly as the resulting reduction in consumption facilitates the further exercise of market power.

Improving Distribution System Performance in Deregulated Electricity Industry Using Phase-Constrained Billing Scheme

Improving Distribution System Performance in Deregulated Electricity Industry Using Phase-Constrained Billing Scheme

Sustainable Transmission Planning in Imperfectly Competitive Electricity Industries: Balancing Economic and Environmental Outcomes

We explore the role of a transmission system operator (TSO) that builds a transmission line to accommodate renewable energy while attempting to lower emissions. A TSO in a deregulated electricity industry can only indirectly influence outcomes through its choice of the transmission line capacity. Via a bi-level model, we show that this results in less transmission capacity and with limited emissions control in a perfectly competitive industry vis-a-vis a benchmark centrally planned system. A carbon charge on industry that fully accounts for the cost of pollution damage leads to a perfect alignment of incentives and maximized social welfare only under perfect competition. By contrast, a carbon charge may actually lower social welfare under a Cournot oligopoly as the resulting reduction in consumption facilitates the further exercise of market power.

Determination of ATC Using DCPTDFs Based Approach in Deregulated Market

Deregulated electricity industry aims to create a competition in market to trade electricity, which gives new opportunities to deal with technical challenges of market participants and power system researchers. The benefits are efficient capacity expansion planning, cheaper electricity, cost minimization, and better services. For better transmission services support in electricity industry and full utilization of transmission assets, Available Transfer Capability (ATC)must be calculated. Available transfer capability (ATC) of transmissionnetwork is the extra amount of power transfer that can betransmitted between the buyer bus and seller bus without any loss ofsecurity. For proper operations of system under the varioustransactions, ATC calculations must be fast andaccurate enough. In this paper by using DCPTDF scheme the ATC is calculatedwith and without line contingency caseand then the corresponding values of ATC are compared. The multiple line contingencies and their effecton the value of ATC are shown. The above said methodology is implemented on IEEE 24-bus test system.

Transmission and Wind Investment in a Deregulated Electricity Industry

Adoption of dispersed renewable energy technologies requires transmission network expansion. Besides the transmission system operator (TSO), restructuring of electricity industries has introduced a merchant investor (MI), who earns congestion rents from constructing new lines. We compare these two market designs via a stochastic bi-level programming model that has either the MI or the TSO making transmission investment decisions at the upper level and power producers determining generation investment and operation at the lower level while facing wind power variability. We find that social welfare is always higher under the TSO because the MI has incentive to boost congestion rents by restricting capacities of transmission lines. Such strategic behavior also limits investment in wind power by producers. However, regardless of the market design (MI or TSO), when producers behave à la Cournot, a higher proportion of energy is produced by wind. In effect, withholding of generation capacity by producers prompts more transmission investment since the TSO aims to increase welfare by subsidizing wind and the MI creates more flow to maximize profit.

California here we come?

John M. Legge explains why a privatised and deregulated electricity industry fails to deliver its promised improvements.

New transmission charges allocation using sensitivity factor methodology

Deregulation of electricity industry aims at creating a competitive market to trade electricity, which generates a host of new technical challenges to market participants and power system researchers. One of the major challenges is to establish a cost for system services on a nondiscriminatory basis. In this paper, the evaluation of transmission cost based on sensitivity factor method such as AC power transfer distribution factor (ACPTDF) method is conducted for bilateral and multilateral transactions. The transacted power is estimated by using ACPTDF method for each transaction. The advantages of the proposed methodologies are demonstrated on sample 6-bus, IEEE 30-bus and Indian Utility 69-bus systems. The solutions provide a better pricing approach that can provide a more reasonable economic indicator for transmission cost.

A New Transmission Charges Allocation using Sensitivity Factor Methodology

Deregulation of electricity industry aims at creating a competitive market to trade electricity, which generates a host of new technical challenges to market participants and power system researchers. One of the major challenges is to establish a cost for system services on a non-discriminatory basis. In this paper, the evaluation of transmission cost based on sensitivity factor method such as AC power transfer distribution factor (ACPTDF) method is conducted for bilateral and multilateral transactions. The transacted power is estimated by using ACPTDF method for each transaction. The advantages of the proposed methodologies are demonstrated on sample 6-bus, IEEE 30-bus and Indian Utility 69-bus systems. The solutions provide a better pricing approach that can provide a more reasonable economic indicator for transmission cost.

Retail competition in electricity supply—Survey results in North Carolina

Residential retail competition in electricity supply was introduced in many countries and some US states as part of electricity industry deregulation. Following problems in the electricity market in California in 2000/2001 many US states, including North Carolina, suspended their deregulation agenda. Recent technological advances have made competition more viable, so we ask if NC should reconsider deregulation and retail competition. The welfare benefits will depend on consumers’ willingness to switch suppliers and the potential for value added innovations. In electricity and industries such as pay-tv and telecommunications consumers are ‘sticky’, remaining with their current supplier even though rivals offer savings. Moreover, some analysts question the likelihood of significant welfare improvements from retail competition. We survey residents in two NC counties focusing on: (i) households’ knowledge of and interest in retail competition, (ii) factors that would encourage them to switch suppliers and (iii) the required savings to encourage switching. About 50–65% of respondents would favor retail competition in NC. Demographic variables and experience switching in other industries affect opinions and the savings required to incent switching. We conclude the estimated rate reduction to encourage competitive switching will be hard to achieve in NC as long as rates remain below the national average.

Hybrid Mutation Particle Swarm Optimisation method for Available Transfer Capability enhancement

A Hybrid Mutation Particle Swarm Optimisation (HMPSO) technique for improved estimation of Available Transfer Capability (ATC) as a decision criterion is proposed in this paper. First, this is achieved by comparing a typical application of the Particle Swarm Optimisation (PSO) technique with conventional Genetic Algorithm (GA) methods. Next, a multi-objective optimisation problem concerning optimal installation and capacity allocation of Flexible AC Transmission Systems (FACTSs) devices is presented and demonstrated.Modern heuristic techniques such as PSO have been demonstrated to be suitable approaches in solving non-linear power system problems. The outcome of this research further demonstrates that with better utilisation of FACTS devices, it is possible to improve transmission capabilities.The motivation of this research is a direct consequence of the deregulation of electricity industries and power markets worldwide. The current deregulated environment provides transmission systems operators (TSOs) with more options when procuring transmission services.The effectiveness of the proposed algorithm is demonstrated across a range of case studies, and the results are validated through analyses conducted on IEEE 30-bus and 57-bus test systems.

GENCOs multiperiod expansion model in a competitive electricity market

Over the past two decades, several countries have restructured their electricity industry by significantly reducing the government’s role in the ownership and management of energy sector. The generation sector was the first activity of the vertically integrated industry to be open for the competition and therefore, it presents the highest level of competitiveness and experience. In the new restructured electricity markets, the objective of each generation company (GENCO) is to maximise its total expected profit over a planning horizon while following the grid-code and system operators’ directive for the safe operation of the power system. In the expansion plan of generating companies, the problem is to be reformulated incorporating several uncertainty factors such as demand growth, the volatility of market prices for electricity and fuels, delay in project completion, financial constraints, etc. In this paper, a long-term multi-period expansion model for a generation company operating in the deregulated electricity industry is presented. The effectiveness of the proposed approach is demonstrated on numerical examples.

Joint energy and reserve dispatch in a multi-area competitive market using time-varying differential evolution

In a deregulated electricity industry, competitive bidding for energy and reserve is increasingly gaining importance and playing a decisive role in maintaining system reliability. The transmission capacity limits have a significant impact on market cost, therefore these limits should also be considered while optimizing the joint dispatch. In this paper, a detailed comparison of classical differential evolution (DE) mutation strategies is carried out to study the role of tuning parameters. For avoiding the time and labor lost in tuning DE parameters, an improved DE algorithm with time varying chaotic mutation and crossover is proposed for solving the multi-product, multi-area market dispatch problem with physical and operational constraints. The proposed approach effectively handles the complex constraints like reserve requirements, zonal power balance constraints, area spinning reserve constraints, tie-line constraints and reserve and capacity coupling constraints. The efficiency and accuracy of the proposed algorithm is tested on two different test systems and is found to be better than classical DE in terms of convergence behavior and solution quality.

The political economy of energy regulation in OECD countries

This paper examines the effect of government ideology, political factors and globalization on energy regulation in electricity and gas industries using the bias-corrected least square dummy variable model in a panel of 23 OECD countries over the period of 1975–2007. We find that left-wing governments promote regulation in gas and electricity sectors. Also, less politically fragmented institutions contribute to deregulation of gas and electricity industries. Long tenures of incumbent government have limited impact on regulation in electricity sector, while it is associated with an increase in regulation of gas sector. Further, we find that higher political constraints and more globalized countries lead to deregulation in electricity and gas sectors. We discover that economic and social integration are the forces that promote deregulation in the gas industry, whereas political integration advance deregulation in the electricity industry. We emphasize that political economy factors are important determinants of energy regulation.

Neural-based electricity load forecasting using hybrid of GA and ACO for feature selection

Due to deregulation of electricity industry, accurate load forecasting and predicting the future electricity demand play an important role in the regional and national power system strategy management. Electricity load forecasting is a challenging task because electric load has complex and nonlinear relationships with several factors. In this paper, two hybrid models are developed for short-term load forecasting (STLF). These models use “ant colony optimization (ACO)” and “combination of genetic algorithm (GA) and ACO (GA-ACO)” for feature selection and multi-layer perceptron (MLP) for hourly load prediction. Weather and climatic conditions, month, season, day of the week, and time of the day are considered as load-influencing factors in this study. Using load time-series of a regional power system, the performance of ACO + MLP and GA-ACO + MLP hybrid models is compared with principal component analysis (PCA) + MLP hybrid model and also with the case of no-feature selection (NFS) when using MLP and radial basis function (RBF) neural models. Experimental results and the performance comparison with similar recent researches in this field show that the proposed GA-ACO + MLP hybrid model performs better in load prediction of 24-h ahead in terms of mean absolute percentage error (MAPE).